University of Southern California Dissertations and Theses

Translating two physical activity programs for older adults into home- and community-based settings: "Active Start" and "Healthy Moves for Aging Well"

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Translating two physical activity programs for older adults into home- and community-based settings: "Active Start" and "Healthy Moves for Aging Well"

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TRANSLATING TWO PHYSICAL ACTIVITY PROGRAMS FOR OLDER ADULTS
INTO HOME- AND COMMUNITY-BASED SETTINGS:
“ACTIVIE START” AND “HEALTHY MOVES FOR AGING WELL”

by

Tingjian Yan
________________________________________________________

A Dissertation Presented to the
FACULTY OF THE GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF PHILOSOPHY
(GERONTOLOGY)

May 2009

Copyright 2009 Tingjian Yan

ii
DEDICATION

To mom Christine for her unconditional love and support

To my father for encouraging me to pursue my dreams

To Patricia for her great friendship and having me as part of the family

To Kate, the best mentor I have ever had

iii

ACKNOWLEDGEMENTS

I would like to acknowledge and extend my heartfelt gratitude to many
people who have contributed to my professional growth and who have shaped my
ability to pursue my dream of getting a Ph.D. First, I would like to give my special
thanks to my dissertation chair and mentor, Dr. Kate Wilber, who believed in me
and supported me unconditionally for four years in the doctoral program. Kate, you
are the best mentor I have ever had. I will always be indebted to you for your
encouragement, direction, and dedication to my success. I would also like to thank
the two other members of my dissertation committee, Dr. Jon Pynoos and Dr. Mike
Nichol, for their valuable input and encouragement in completing my dissertation.
I want to express my gratitude to thank the faculty of the Davis school of
Gerontology, Dr. Merrill Silverstein, Dr. Eileen Crimmins, Dr. Norella Putney, and
Dr. Susan Enguidanos, who inspired me and provided me many opportunities for
learning and collegiality. Most especially, I am grateful to Dr. Phoebe Liebig. Her
encouragement helped me to survive and succeed from the first course I took
when I arrived in this country. This, in turn, gave me great confidence in completing
the rest of my courses in the doctoral program.
My colleagues, friends, and staff at the Davis school of Gerontology have
been supportive and stimulating during the past four years. I wish to thank Dr.
Aaron Hagedorn, Dr. Gretchen Alkema, and Dr. Christy Nishita, who shared their
experience and gave me their guidance throughout the program. I am grateful to
Zachary Gassoumis, Adria Emberson, Kathryn Thomas, Lori Klaidman, and other

iv
doctoral students for their help in many ways. Most especially, I want to thank
Adriana Ruggio for sharing my ups and downs in the doctoral experience. Our
friendship is everlasting.
My family deserves credit for enabling me to fully devote so much time to
my work. I would like to thank Mom Christine for her endless support and sacrifice.
Without her, my success in the program would not have been possible. I thank my
family in China for their support and encouragement, as I have pursued my
dreams. I miss you all very much. Additionally, I could never give enough thanks to
my best friend and American family, Patrica O’Neill, who has also been there for
me. I am honored to be part of your family.
Last but not least, I would like to thank many people who contributed to the
development of the interventions: Rosa Aguirre, June Simmons, Jennifer
Wieckowski, and their assistants.

v
TABLE OF CONTENTS

Dedication

ii
Acknowledgements

iii
List of tables v
List of Figures vi
Abstract

vii
Chapter I: Introduction

1
Chapter II: Will sedentary older adults benefit from
community-based exercise? Results from the Active
Start program
10

Chapter III: Results from the Healthy Moves program: Changes
in health outcomes

27
Chapter IV: Motivating frail older adults to exercise: Coaching
matters

41
Chapter V: Discussion

54
Bibliography 58

vi
LIST OF TABLES

Table 1 Participant characteristics at pretest of the Active Start
intervention

19
Table 2 Unadjusted mean pre-and post-test scores with standard
deviations for Active Start
21
Table 3 Adjusted mean pre- and post-test scores with standard
errors for the intervention group of Active Start
23
Table 4 Participant characteristics at pretest of the Healthy Moves
intervention

36
Table 5 Unadjusted changes of health outcomes from pre-test to
3-Month post-test for Healthy Moves

37
Table 6 Adjusted mean pre-and post-test scores with standard
errors for Healthy Moves

38
Table 7 Characteristics of the sample for Healthy Moves by
Coaching

47
Table 8 Changes of functional performance from pre-test to
post-test for Healthy Moves

50
Table 9 Multiple regression models predicting changes of arm curl
and seated steps-in-place for Healthy Moves

51

vii
LIST OF FIGURES

Figure 1: Criteria in reporting health behavioral interventions
Utilizing the RE-AIM framework

8
Figure 2: CONSORT diagram of Active Start

17
Figure 3: CONSORT diagram of Healthy Moves 35

viii
ABSTRACT
Most of the existing physical activity intervention studies among older adults
have not been designed to change their lifestyles or activity behaviors, and have
not targeted frail, underserved older adults. Two physical activity promotion
programs entitled Healthy Moves for Aging Well (“Healthy Moves”) and Active
Start were developed to address this research gap. This dissertation evaluated the
effectiveness of these two physical activity programs.
Outcomes were analyzed using a within-group, pretest-posttest design. For
the Active Start program, paired t-tests were employed to analyze unadjusted
mean changes in physical performance measures from pretest to 20-week
posttest. Repeated measures ANCOVAs (using SAS proc mixed) were then
conducted to calculate the adjusted mean change for the intervention group. For
the Healthy Moves program, paired t-tests and nonparametric Wilcoxon signed
rank tests were employed to analyze the changes in health outcomes from pre-test
to 3-month post-test, depending on the distribution and types of variables. Multiple
regression models were conducted to examine whether different coaching
strategies were associated with changes in exercise performance.
Results show that participation in Active Start produced significant
improvement in physical performance measuring strength, flexibility and balance
among overall participants and by race/ethnicity. As a home-based low-intensity
strength training program, Healthy Moves can motivate high-risk, ethnically
diverse older adults to exercise. Participants had significant decline in the number
of falls and pain level and this decline was found among participants who improved

ix
their exercise performance. Individuals with the combination of face-to-face and
phone coaches had better exercise performance, compared to those motivated by
phone coaching alone.
Guided by the REAIM framework, this dissertation research reported on the
target population and the recruitment strategies (“Reach”), examined the
“effectiveness” of the two interventions, described the participation rate and
characteristics of intervention agents (“Adopt”), and identified essential
intervention elements (“Implementation”). Strategies for building sustainable
evidence-based health programs should be addressed in future studies to
maintain the benefits of physical activity for older adults over time (“Maintenance”).

1
CHAPTER I: INTRODUCTION

A. Research Background
A decline in fertility and a 20-year increase in the average life span during
the second half of the 20th century have resulted in significant population changes
in the World and in the United States in particular (United Nations, 2002). With the
aging of the 78-million baby boomers, people who were born between 1946-1964,
the United States will be experiencing unprecedented increases in the number and
proportion of its elderly population in the first half of the 21
st
century. Between 2000
and 2050, the number of older people aged 65 and over is projected to grow from
35 million to 86.7 million. The proportion of the elderly population will increase from
12.7% to 20.7% of the total population. Moreover, during the same period, the
oldest-old, those aged 85 and over, will be the most rapidly growing elderly age
group. The number of the oldest old is projected to increase from 4.2 million in
2000 to 20.9 million in 2050. The oldest old represented 12.1% of the elderly
population in 2000 and 1.5% of the total population. In 2050, they are projected to
be 24% of the elderly population and 5% of the total population (US Bureau of the
Census, 2004).
As the number of older people burgeons, a major clinical and public health
priority is to maintain the functional independence and well being of these older
adults. Participation in regular physical activity and exercise is a prominent
strategy in improving and maintaining the health and well-being of older adults and
has been proven to benefit a variety of health outcomes. The consensus is that
regular physical activity and exercise reduces the risk of chronic conditions among
2
older adults such as osteoporosis, coronary heart disease, hypertension, colon
cancer, and type 2diabetes (American College of Sports Medicine [ACSM], 1998).
It can improve functioning through increased muscle strength, aerobic capacity,
flexibility, and balance (Keysor & Jette, 2001). And it may decrease the risk of falls
and injuries from falls (Messier et al., 2000; American Geriatrics Society [AGS] et
al., 2001). Furthermore, physical activity may reduce the symptoms of depression
and anxiety disorders (Brosse, Sheets, Lett, & Blumenthal, 2002; Dunn, Trivedi, &
O’Neal, 2001), pain (AGS, 2002), and sleep problems (King et al., 1997).
Despite the numerous benefits of regular physical activity and exercise,
older adults are the least physically active segment of the adult population (Center
for Disease Control and Prevention [CDC], 2003). To promote and maintain
health, older adults are recommended to engage in moderately intense aerobic
physical activity for a minimum of 30 minutes, 5 days per week, or vigorously
intense aerobic activity for a minimum of 20 minutes, 3 days per week (Nelson et
al, 2007). However, only a small percentage of the older adults are currently
meeting this recommendation. For instance, only 16 percent of individuals aged 65
to 74 reported participating in 30 minutes of moderate activity 5 or more days per
week and only 12 percent of those 75 and older reported such exercise habits.
Only 13 percent of individuals between ages 65 and 74 reported participating in
vigorous physical activity for 20 minutes 3 or more days per week, and only 6
percent of those 75 and older reported such exercise (U.S. Department of Health
and Human Services [USDHHS], 2000).
3
Interventions in community settings to promote physical activity have
emerged as a critical piece in the overall strategy to increase physical activity in the
United States (Task Force on Community Preventive Services [TFCPS], 2002). A
large number of physical activity intervention studies in community settings have
been conducted to promote physical activity among older adults and to improve
their health and functional independence. These interventions have been found in
various formats, including supervised home-based activity (McMurdo &
Johnstone, 1995), group/class-based activity (Stewart et al., 1997;Wallace et al.,
1998) or a combination of group/class- and home-based activity (King et al, 1997;
Stewart et al., 1997).
Notwithstanding these efforts, there has been an inadequate translation of
research findings into intervention strategies that are practical, and that can be
widely incorporated into broad home and community-based settings (Glasgow,
Lichtenstein & Marcus, 2003). Most of the existing physical activity intervention
studies among older adults have not been designed to specifically change their
lifestyles or activity behaviors, that is, to help participants make regular physical
activity or exercise a routine part of their lives (King, Rejeski, & Buchner, 1998;
Stewart et al., 2001; Conn, Minor, Burks, Rantz, &Pomeroy, 2003). Therefore,
there is a great need for continued research on the effectiveness of physical
activity interventions to help people maintain behavior change (Marcus et al.,
2006). In addition, few studies on the effectiveness of physical activity promotion
interventions have targeted or included substantial numbers of important diverse
subgroups, such as frail older adults, underserved populations, which are defined
4
as racial or ethnical minorities or individuals with low socioeconomic status (SES),
and the oldest-old (King et al., 1998; Glasgow, et al., 2003; Marcus et al., 2006).
Information about physical activity among these diverse subgroups is essential for
health professionals to develop targeted strategies, design interventions, and
engage in the marketing of physical activity programs (Prohaska et al., 2006).
To address this serious gap, two physical activity promotion programs
entitled Healthy Moves for Aging Well (“Healthy Moves”) and Active Start were
developed under the supervision of the Partners in Care Foundation and of Los
Angeles City Department of Aging respectively. The purpose of the dissertation is
to evaluate the outcomes of the Active Start and Healthy Moves programs and to
determine the effectiveness of implementing the two physical activity promotion
programs for older adults into in-home and community-based settings. The
specific aims of the dissertation are:
1. to evaluate the physical functioning outcomes of the Active Start program
among overall participants and by race/ethnicity;
2. to evaluate changes in outcomes of the Healthy Moves program; and
3. to compare two different coaching channels used in the intervention- the
combination of face-to-face with phone coaching versus phone coaching
alone) on changes in exercise performance among participants in the
Healthy Moves program.
B. Conceptual Framework: the RE-AIM model

The National Institute of Health has identified two areas of translational
research (Rohrbach, Grana, Sussman, & Valente, 2006). Type 1 translation
5
applies to the development and testing of treatment and prevention approaches
based on discoveries generated through laboratory and preclinical research. The
translational research of physical activity interventions is a type 2 translation,
which is aimed at enhancing the adoption of effective practices in the community.
Successful translation and dissemination of effective physical activity interventions
into communities and of the public health impact of such initiatives is best served
by the use of RE-AIM model as a conceptual framework (Glasgow, Vogt, &Boles,
1999). The RE-AIM framework provides a systematic way to evaluate health
promotion interventions (http://www.re-aim.org). RE-AIM is an acronym for Reach,
Efficacy or Effectiveness, Adoption, Implementation, and Maintenance.
Reach refers to the participation rate among those approached and the
representation of participants. Factors determining Reach are the size and
characteristics of the potential audience and the barriers to participation (e.g., cost,
social and environmental context, necessary referrals, transportation, and
inconvenience). Efficacy or Effectiveness pertains to the impact of an intervention
on important outcomes, including potential negative effects, quality of life, and
economic outcomes. Adoption operates at the setting level and concerns the
percentage and representation of organizations or settings that will conduct a
given program. Factors associated with Adoption include political and cultural fit,
cost, level of resources and expertise required, and how similar a proposed service
is to current practices of an organization. Implementation refers to intervention
integrity, or the quality and consistency of delivery. At the setting level,
Implementation refers to the intervention agents' fidelity to the various elements of
6
an intervention's protocol, including consistency of delivery as intended and the
time and cost of the intervention. At the individual level, Implementation refers to
clients’ use of the intervention strategies. Finally, Maintenance operates at both
the setting or organizational level and the individual level. At the setting level,
Maintenance refers to the extent to which a program or policy becomes
institutionalized or part of the routine organizational practices and policies. At the
individual level, Maintenance has been defined as how well behavior changes hold
up in the long term (Glasgow et al., 2003).
It is important for researchers to report health behavioral intervention
studies in a transparent way. To improve the quality of reporting the results of
randomized clinical trials, the CONSORT statement or the Consolidated Reporting
of Standard Trials was developed with 22 criteria and a flow diagram (Moher,
Schulz, & Altman, 2001). The existing CONSORT criteria are focused mainly on
the maintenance of internal validity, namely the degree to which the intervention
establishes the cause-and-effect relationship between the treatment and the
observed outcome. However, no guidance is provided for reporting the external
validity, known as the generalizability of the intervention findings. Glasgow and
colleagues (2003) added 7 elements to the existing CONSORT criteria and
balanced internal and external validity in the RE-AIM framework.
Figure 1 shows the criteria for reporting health behavioral intervention
studies utilizing the RE-AIM framework. Specifically, translating physical activity
research findings into broad community settings requires researchers to show how
the program or study reaches the targeted population through reporting the rate of
7
exclusion (Reach), and recruitment strategies, to describe the participation rate
and characteristics of intervention agents (Adopt), to ensure that the intervention is
delivered properly, for example, by identifying essential/core elements of the
intervention (Implementation), and to report results of maintenance not only on the
individual level but also on the program level (Maintenance) (Glasgow et al., 2003;
Prohaska & Peters, 2007). The evaluation work of this dissertation study is guided
by the RE-AIM framework.
C. Contribution to the Literature
This dissertation contributes to the scientific literature in two interrelated
ways. First, as the basis for this study, results from this study will report the
effectiveness of two physical activity programs for changing behaviors of
sedentary older adults and in improving physical functioning among low-income,
high risk older adults in the community. Second, as discussed above, there is a
great need to translate physical activity research findings into broad in-home and
community-based settings. And little information is known about physical activity
intervention programs for frail, underserved populations. Therefore, the larger
contribution of the dissertation to the literature is that it will provide the evidence
and recommendations for implementing physical activity programs in typical
community settings serving frail, underserved populations.
8
Figure 1. Criteria for Reporting Health Behavioral Interventions Utilizing the
RE-AIM Framework

Reach

Effect/Efficacy

Adoption

Implementation

Maintenance
 Show the target
population to which the
study intends to
generalize;
 Report the rate of
exclusion, the
participation rate among
those eligible, and the
representation of
participants;
 Report on methods of
recruiting study settings,
including exclusion rate,
participation rate among
those approached, and
representation of settings
studied;
 Describe the participation
rate and characteristics of
those delivering the
intervention. State the
population of intervention
agents that one would
see eventually
implementing the
program and how the
study interventions
compare with those who
will eventually deliver the
intervention;
 Report the extent to
which different
components of the
intervention are delivered
as intended in the
protocol;
 Report the specific time,
and costs required to
deliver the intervention;
 Report on organizational
level of continuance,
discontinuous or
adaptation in modified
form of the intervention
once the trial is
completed, and
individual-level
maintenance results.
9
D. Organization of the Dissertation
This chapter provided the research background and introduced the
conceptual framework for the dissertation research. Chapter II reports the
outcomes of the Active Start program. Chapter III reports changes in health
outcomes from the Healthy Moves program. Chapter IV reports the differential
effects of two coaching channels, the combination of face-to-face with phone
coaching versus phone coaching alone, on changes in the exercise performance
among participants in the Healthy Moves program. Chapter II, III and IV are written
as stand alone chapters. Chapter V provides a discussion of the dissertation and
future directions for translational research based on findings from this work.

10
CHAPTER II. WILL SEDENTATY OLDER ADULTS BENEFIT FROM
COMMUNUTY-BASED EXCERSISE? RESULTS FROM THE ACTIVE START
PROGRAM
A. Introduction

Regular physical activity is an important determinant of health and
functioning for people of all ages (ACSM, 1998). Physical activity levels, however,
are inversely associated with age, such that individuals aged 50 years and over
are the most sedentary segment of the adult population (USDHHS, 1996). About
28% to 34% of adults aged 65 to 74 and 35% to 44% of adults aged 75 or older are
inactive meaning that they engage in no leisure-time physical activity (Agency for
Healthcare Research and Quality, 2002). Moreover, the prevalence of physical
inactivity varies by race and ethnicity, with Whites more likely to engage in
leisure-time physical activity than African-Americans and Hispanics (CDC, 2005).
Various interventions designed to increase and enhance physical activity
have been tested among predominately sedentary older adults. Individually
adapted behavior-change programs have been found to be effective and strongly
recommended for increasing physical activity at the community level (TFCPS,
2002). Most of the existing community-based physical activity interventions,
however, have not been designed specifically to change the lifestyle or activity
behavior of older adults (King et al., 1998; Stewart et al., 2001; Conn et al., 2003),
and have not included a meaningful numbers of ethnic minority or lower-income
individuals (King et al., 1998; Glasgow et al., 2003; Yancey et al., 2004; Marcus et
al., 2006). There is a need for continued research on the effectiveness of physical
11
activity interventions that help people change their behavior and sustain their
fitness efforts (Marcus et al., 2006). Information about physical activity among
diverse subgroups is essential for health professionals to describe, target and
market physical activity programs (Prohaska et al., 2006).
Active Start, was designed to change physical activity behavior among
predominately sedentary and racially/ethnically diverse community-dwelling older
adults. The purpose of the study was to assess the effectiveness of Active Start in
improving physical performance among participants overall and by race/ethnicity.
B. Methods
Target Population
Active Start included community-dwelling older adults aged 50 years and
over. The intervention targeted those who were sedentary or under-active, with
physical activity levels less than the recommended moderate physical activity of at
least 30 minutes per session on 5 or more days per week or vigorous physical
activity of at least 20 minutes 3 or more days per week (Nelson et al, 2007).
Participants were recruited from community senior centers and senior housing
facilities in the city of Los Angeles.
Design
A quasi-experimental design was used with an intervention group and a
small waitlist comparison group. Functional performance was measured at
pre-test and 20-week post-test for both groups. When the intervention group had
completed the 20-week intervention, participants in the waitlist comparison group
were invited to start the 20-week fitness program. The project began on
12
September 30, 2004 and was completed on September 29, 2008. The study was
approved by the institutional review board of the University of Southern California
and all study participants completed a written informed consent form.
Recruitment Strategies
Active Start used a multifaceted approach to recruit participants. To
improve the likelihood of recruiting success, the project coordinator identified
potential participating sites by examining their demographics and unmet needs.
The project coordinator then contacted directors of potential sites and scheduled
presentations about the program fundamentals, benefits, and the necessary
commitments of the directors and other staff.
Active Start also recruited peer lay leaders to motivate and train
participants. Although a previous evolution of the Active Start program utilized
professionally certified instructors who received payment for leading classes,
some participants indicated that the fitness professionals did not understand and
share the daily challenges of the participants. To address this concern, the lay
leader approach was developed. Potential lay leaders were selected based on
their interests, ability to participate in the two-day training session, commitment to
completing the program, and potential to lead and motivate participants.
Background in health or fitness was not required. Participating site directors and
other staff helped identify potential peer lay leaders within the host agency’s
community. Strategies employed to recruit lay leaders included presentations,
word of mouth, Internet postings and print ads. A total of eight lay leaders were
recruited, trained and completed the 20-week intervention.
13
In addition to project presentations, flyers, brochures/catalogs, and word of
mouth were used to recruit potential participants. Flyers and brochures in English
and Spanish were distributed at host sites, neighboring facilities where seniors
congregate, health fairs, or other community events. The project coordinator and
other staff encouraged project participants to bring their friends or any interested
potential participants to the project.
The Exercise Intervention
Well-structured, center-based programs using behavior change strategies,
such as self-monitoring, goal setting, feedback, and self-evaluation, have been
successful in increasing physical activity among healthy and often sedentary
community-dwelling older adults (King et al.,1997; Taylor, Baranowski, &
Rohm-Young,1998; Brawley, Rejeski, & King, 2003). To help participants develop
behavioral skills needed to adopt an active lifestyle, Active Start used two
evidence-based programs, Active Living Every Day (ALED) and ExerStart. ALED,
developed by the Cooper Institute, is a behavior change program tested in several
randomized controlled trials (Dunn et al., 1999; Sevick et al., 2000). As a 20-week
program, it is delivered in a group setting in which participants meet one hour a
week during the 20 weeks to set goals, identify barriers, and establish social
support systems (Dunn et al., 1997; 1999).
The second component of Active Start, ExerStart, is a low-intensity program
designed specifically for sedentary older adults. It is comprised of 43 exercises
focusing on aerobic strength (e.g. standing squats), flexibility (e.g. point and flex
ankles), and balance (e.g. around the clock weight shifts). Participants attend
14
class twice a week for a total of 90 minutes per week for 20 weeks. Each class
consists of a 5-minute warm-up, 10-minute aerobic stretch, 15-minute strength,
5-minute cool-down/balance, and a10-minute flexibility training. In the present
study, all exercises were performed to culturally preferred music chosen by the
group or the lay leader. Resistance bands were used for some of the exercises. To
help reinforce class content, participants were asked to take home a handout that
included a safe exercise they could practice and complete at home, at the end of
each class. The Senior Fitness Test (SFT) (Rikli & Jones, 1999) was used to
measure the efficacy of the 20-week curriculum. The SFT is a 7-item battery
measuring lower-body strength (chair stand), upper-body strength (arm curl),
aerobic endurance (6-minute walk, and 2-minute step), lower-body flexibility (chair
sit-and-reach), upper-body flexibility (back scratch), and balance (8-foot
Up-and-Go). Due to the limited space, the 6-minute walk test was not included.
The remaining six tests were measured before and after the ES intervention. To
ensure that lay leaders were able to complete the SFT for each participant, these
items were broken up over three classes, with two SFT items administered in each
of the first three classes of the intervention. ES introduced participants gradually to
exercises with simpler exercises and fewer repetitions of each exercise
recommended in the earlier stages of the program.
Training Procedure
Prior to implementation, all lay leaders attended a two-day training covering
the two Active Start components. The first day focused on the ALED program.
Training was conducted by a master trainer certified through Human Kinetics. The
15
scripted training exposed lay leaders to issues of group dynamics, facilitation, and
dealing with difficult situations. All lay leaders had to successfully complete an
exam to be certified by Human Kinetics. The second day of training focused on the
ExerStart program. Through the training, lay leaders learned how to lead each
exercise in the ExerStart curiculum, to conduct the SFT and practiced leading a
mock exercise session.
Measures and Analysis
Data were analyzed using a within-group, pretest-posttest design to
compare change in the intervention group overall and by race/ethnicity to change
in the comparison group.
Participation Rates. The overall participation rate was computed as the total
number of participants included in the pretest analysis divided by the number of
participants who were eligible for the study. The drop-out rate was computed as
the number of participants who dropped out of the study by the 20-week posttest
divided by the total number of participants in the pretest. Chi-square tests and t
tests were used, as appropriate, to assess differences between participants who
completed the program and those who did not.
Physical performance. Physical performance was measured by six SFT
items. Changes of physical performance from pretest to posttest were first
measured using paired t-test to calculate the unadjusted mean change for the
intervention group and the wait-list comparison group as well as across
race/ethnicity in the intervention group. Repeated measures ANCOVAs (using
SAS proc mixed) were then conducted to calculate the adjusted mean change for
16
the overall intervention group controlling for physical activity level, age, gender,
race/ethnicity, and self-reported health status.
C. Results
Sample Description
As shown in Figure 2, a total of 220 participants were screened into the
study. Three who were too physically frail to do the exercises were excluded.
Among those eligible (n=217), 9 declined to participate and 208 (96%) were
included in the pretest analysis.
Of the 208 participants who enrolled in the study, 151 were allocated to the
intervention group and 57 to the waitlist comparison group. Of the 151 participants
in the intervention group, 140 (93%) completed the study. Of the 11 (7%) who did
not, 7 identified health problems as the reason; 3 left the study without any reasons
given; 1 could not keep up with the exercise. Of the 58 participants in the waitlist
comparison group, 16 (28%) remained in the study until their intervention started
20 weeks later and 41 left the study prior to the 20-week period. Ten participants
dropped out because they were no longer interested and two senior centers with
31 participants left the study, because they could not locate enough staff to train
the participants.
17
Figure 2. CONSORT Diagram of Active Start

Assessed for Eligibility (n=220)
Eligible (n=217)
 Declined to
participate (n=9)
Included in Pre-test Analysis (n=208)
Allocated to Intervention
Group (n=151)
Allocated to Waitlist
Comparison Group
(n=57)
Included in Post –test
Analysis (n=140)
 SFT test not
administered (n=6)
Included in Post –test
Analysis (n=16)
Lost to Post-test (n=41)
 Not interested in the
study (n=10)
 2 sites dropped study
(n=31)
Lost to Post-test (n=11)
 Health problems (n=7)
 No reason given (n=3)
 Couldn’t keep up with the
exercise (n=1)
Excluded (n=3)
 Not Meeting
Inclusion Criteria
(n=3)
18
Analyses were further conducted to compare characteristics between those
who completed and those who dropped out in the wait-list comparison group (table
not shown). Although no significant differences were found in age, gender,
education and self-rated health, there was a significant racial/ethnic difference
between the two groups (p<.001). The majority of the participants who left the
study were Hispanics (46%), and the majority who completed were Blacks (81%),
reflecting the composition of the centers that participated versus the two that
withdrew.
Baseline Characteristics
Table 1 shows the characteristics of participants at pretest. The mean age
was 73 years; 82 percent were female; more than half were Hispanics. About half
had an education level below high school. Although more than 65 percent rated
their health as good, very good, or excellent, only one third engaged in regular
physical activity at pretest.
No significant differences were found between the intervention group and
the waitlist comparison group in terms of age, gender, education and self-rated
health. However, there was a significant racial/ethnical difference between the two
groups (p<.01). The majority of the participants in the intervention group were
Latinos (56%), whereas in the waitlist comparison group, African-Americans
accounted the largest percentage (39%) and Latinos comprised 35%.

19
Table 1. Participant Characteristics at Pretest of Active Start

Total
(n=208)
Intervention
Group
(n=151)
Comparison
Group
(n=57)
n % n % n %
Age (mean, SD) 72.88(8.83) 73.52(9.31) 71.23(7.27)
Gender
Female 171 82.21 127 84.11 44 77.19
Male 37 17.79 24 15.89 13 22.81
Race/ethnicity
White 47 22.60 38 25.17 9 15.79**
Black 45 21.63 23 15.23 22 38.60
Hispanic 105 50.48 85 56.29 20 35.09
Other 4 1.92 2 1.32 2 3.51
Missing race 7 3.37 3 1.99 4 7.02
Education
Below High School 95 45.67 76 50.33 19 33.33
High School and above 97 46.63 69 45.70 28 48.12
Missing Education 16 7.69 6 3.97 10 17.54
Self-rated Health
Poor or Fair 60 28.85 43 28.48 17 29.82
Not Poor or Fair 137 65.87 101 66.89 36 63.16
Missing self-rated health 11 5.29 7 4.64 4 7.02
Physical Activity Level
Sedentary 52 25.00 42 27.81 10 17.54
Underactive 77 37.02 52 34.44 25 43.86
Regularly physical active 69 33.17 53 35.10 16 28.07
Missing physical activity level 10 4.81 4 2.65 6 10.53
Note:*p<.05; **p<.01; ***p<.001; P is based on the complete data.

Changes of Physical Performance
Table 2 presents unadjusted mean scores of the six measures for pretest
and posttest. Significant improvement on all SFT measures was found among the
intervention group as a whole, whereas no significant changes were found in the
waitlist comparison group. When analyzed separately by race/ethnicity for the
intervention group, improved scores were found on all of the six SFT measures,
although changes of chair sit-and-reach for Whites and Blacks, and changes of
back scratch for Whites were not statistically significant. The adjusted mean
20
scores of the six measures for pretest and posttest were further calculated for the
entire intervention group, after controlling for pretest physical activity levels, age,
gender, race/ethnicity, and self-reported health status (see table3). Similar trends
were found; participants in the intervention group had significant improvements on
all of the six SFT measures from pretest to posttest. For example, the number of
chair stands in 30 seconds, on average, improved from 9.62 (standard error
(SE)=0.31) to 12.84 (SE=0.31, p<.001). No significant differences were found
across race/ethnicity.

21
Table 2. Unadjusted Mean Pretest and Posttest Scores With Standard Deviations for Active Start
SFT
Intervention Group
Comparison
Group
Total White Black Hispanic
Chair stand, # in 30
Second

n 125 25 18 81
16
Pretest, mean (SD) 9.92(3.51) 10.04(3.06) 9.44(4.74) 9.95(3.36)
10.44(2.90)
Posttest, mean (SD) 13.19(3.61) 12.24(3.28) 13.00(3.97) 13.49(3.63)
10.31(2.52)
t (P value) 15.42(<.0001) 4.69(<.0001) 6.54(<.0001) 13.69(<.0001)
-0.25(0.81)
Arm curl, # in 30 second

n 130 25 21 81
16
Pretest, mean (SD) 11.47(4.17) 13.32(4.03) 12.24(5.17) 10.79(3.75)
10.81(4.32)
Posttest, mean (SD) 16.03(4.57) 17.04(4.80) 17.10(5.13) 15.35(4.21)
10.31(0.70)
t (P value) 14.44(<.0001) 3.89(0.001) 5.49(<.0001) 14.08(<.0001)
-0.44(0.66)
2-min Step, # in 2 minute

n 126 25 17 81
16
Pretest, mean (SD) 68.50(21.61) 72.36(24.45) 61.71(16.32) 68.89(21.45)
60.06(17.95)
Posttest, mean (SD) 89.40(22.24) 91.56(24.11) 83.18(20.55) 89.60(22.23)
64.75(20.04)
t (P value) 15.71(<.0001) 5.58(<.0001) 4.87(0.0002) 14.03(<.0001)
2.08(0.06)
Chair Sit-and-Reach,
inch from toe

n 129 24 21 81
16
Pretest, mean (SD) -2.51(3.88) -1.50(3.86) -2.55(3.34) -2.83(3.99)
-2.41(2.85)
Posttest, mean (SD) -1.20(3.50) -0.33(3.52) -2.14(3.73) -1.20(3.47)
-2.38(3.24)
t (P value) 5.05(<.0001) 1.18(0.25) 0.58(0.57) 7.37(<.0001)
0.07(0.94)

22
Table 2, Continued

Note: for chair sit-and-reach test and back scratch test, the higher (positive) the score, the better the performance
SFT
Intervention
Group
Comparison
Group SFT
Intervention
Group
Comparison
Group
Back scratch, inch from
middle fingers

n 133 27 21 83
16
Pretest, mean (SD) -6.09(5.62) -2.80(5.36) -6.81(4.62) -6.93(5.65)
-7.88(4.23)
Posttest, mean (SD) -4.81(4.79) -2.15(4.68) -5.62(4.02) -5.65(4.68)
-8.81(5.09)
t (P value) 4.10(<.0001) 1.63(0.12) 2.53(0.02) 3.10(0.003)
-1.18(0.26)
8-ft up-and-go, seconds

n 129 25 19 82
16
Pretest, mean (SD) 8.87(4.20) 6.86(2.46) 11.35(5.11) 8.96(4.16)
7.53(6.15)
Posttest, mean (SD) 7.52(3.37) 6.21(1.66) 9.35(5.05) 7.56(3.15)
8.62(2.67)
t (P value) -9.66(<.0001) -2.85(0.001) -6.20(<.0001) -7.54(<.0001)
0.61(0.55)

23
Table 3. Adjusted Mean Pre-and Posttest Scores With Standard Errors for the Intervention Group of Active Start

Note: All means and standard errors were adjusted for physical activity levels, age, gender, race/ethnicity, and self-reported health status.
Pretest, mean (SE)
Posttest, mean
(SE) t (P value)
Chair stand, # in 30 second, (n=116) 9.62(0.31) 12.84(0.31) 15.13 (<.0001)
Arm curl, # in 30 second, (n=120) 11.42(0.35) 15.84(0.36) 14.17(<.0001)
2-min Step, # in 2 minute, (n=115) 66.55(1.90) 86.45(1.89) 14.60(<.0001)
Chair sit-and-reach, inch from toe, (n=118) -2.05(0.57) -0.81(0.57) 4.41(<.0001)
Back scratch, inch from middle fingers,
(n=123) -5.53(0.45) -4.55(0.46) 3.33(0.001)
8-ft up-and-go, seconds, (n=118) 8.75(0.30) 7.49(0.30) -8.94(<.0001)
24
D. Discussion
The majority of empirically evaluated community-based programs have
targeted endurance-oriented activities, such as brisk walking, general aerobic
movement, or conditioning activities, either with or without additional strengthening
and flexibility activities (Wallace, et al., 1998; King, 2001; Van der Bij, Laurant, &
Wensing, 2002). Fewer studies have investigated the combination of strength,
flexibility, and balance training among healthy sedentary older adults (Brawley et
al., 2003). The current study was undertaken to determine if Active Start, a
center-based group exercise program that used a combination of two
evidence-based interventions, was effective in improving strength, flexibility, and
balance in diverse community-dwelling older adults. Results suggest that
participation in Active Start produced significant improvements in physical
performance measuring strength, flexibility, and balance. Moreover, a remarkably
high percentage (93%) of participants in the intervention group completed the
20-week study.
Previous studies have reported difficulties in completing the SFT items in
routine class sessions (Belza et al., 2006). The present study successfully
resolved this challenge by breaking up the six SFT items over three classes, with
two SFT items administered in each of the first three classes of the intervention.
Many existing physical activity interventions have not been able to target or
recruit a meaningful number of ethnic minorities. Ethnic minorities may face such
barriers to participation as their inability to speak or read English, illiteracy in their
native language, and a lack of interpreters or bilingual health care professionals
25
(Brawley et al, 2003). Active Start successfully recruited a large proportion of minority
participants by providing culturally sensitive services, such as bilingual project
coordinators and lay leaders, bilingual handouts, and culturally preferred music.
Some evidence-based interventions have been shown to be less effective
or ineffective in ethnic minority or low-income populations (Yancey et al., 2004). In
contrast, results from the present study showed that Hispanics significantly
improved their physical performance on all of the six SFT items in 20 weeks.
Similar trends were found for Whites and Blacks.
The effectiveness of the Active Start program also hinged on being able to
keep people engaged in exercise. Ninety-three percent of the participants in the
intervention group completed the program. To assist in the maintenance of
physically active lifestyles, it is essential that interventions are tailored to
individuals’ ideas and preferences and that a variety of physical activity options are
made available (Rejeski & Mihalko, 2001). Active Start met participants needs by:
(1) using trained lay leaders who understood and shared the same daily
challenges of the participants; (2) using behavior change principles in ALED; and
(3) using specially designed exercises for the participants.
Several limitations should be noted when applying the results. First, the
evaluation did not use a randomly controlled group. In addition, difficulties were
encountered in sustaining the waitlist comparison group. Older adults were less
motivated to come back for follow-up assessments, when they could not see the
immediate benefit for them. Among the 51 participants recruited in the comparison
group, 31 dropped out due to lack of training staff in the two senior centers. This
26
finding highlighted the importance of support from community centers in physical
activity interventions in community settings.
Despite these challenges, the evaluation indicates that a community-based
physical activity program benefits sedentary, ethnically diverse older adults.
Coupling a behavioral change support group and fitness classes result in
significant improvements in all measures of physical performance. In addition to
the curriculum and the use of lay leaders, Active Start was conducted using
community agencies. The City of Los Angeles Department of Aging used its
network of agencies to recruit lay leaders and participants and to bring the
intervention to its local senior centers. As extensive aging networks exist
throughout the U.S. that could be typed to work with local providers to replicate the
program.
27
CHAPTER III. RESULTS FROM THE HEALTHY MOVES PROGRAM: CHANGES
OF THE HEALTH OUTCOMES
A. Introduction

Research suggests that it is never too late to begin an exercise program
(USDHHS, 1996). A growing body of evidence has shown that regular physical
activity can benefit individuals during their entire life course, regardless of age. Of
particular importance to older adults, physical activity has been demonstrated to
be beneficial on a variety of health outcomes, such as reducing falls (Tinetti et al.,
1994; Messier et al., 2000; American Geriatrics Society, British Geriatrics Society,
and American Academy of Orthopaedic Surgeons Panel on Falls Prevention,
2003), fear of falling (Zijlstra et al, 2007), depression (Dunn et al., 2001; Brosse, et
al., 2002) and pain (American Geriatric Society Panel on Persistent Pain in Older
Persons, 2002).

To promote and maintain health, older adults are recommended to
do moderate-intensity aerobic physical activity for a minimum of 30 minutes five
days per week or vigorous-intensity aerobic activity for a minimum of 20 minutes
three days per week (Nelson et al., 2007). Only a small percentage, however, of
people aged 65 and older, currently meet this recommendation. For example, only
16 percent of individuals aged 65 to 74 reported participating in 30 minutes of
moderate activity five or more days per week and only 12 percent of those 75 and
older reported such exercise. Only 13 percent of individuals between the ages of
65 and 74 reported engaging in vigorous physical activity for 20 minutes three or
more days per week, and only six percent of those 75 and older reported such
exercise (USDHHS, 2000).

28
Existing evidence suggests that physical activity programs may appeal to older
adults, when they are tailored to individuals’ preferences (AARP, 2001) and
include activities that are more moderate in intensity, simple and convenient to
engage in (King, 2001). A majority of older adults prefer programs that can be done
on their own outside of structured classes or groups but with some level of
instruction (King, 2001; Prohaska et al., 2006). Home-based programs allow
individuals to exercise at their convenience in the comfort of familiar surroundings
(Jette, et al, 1999). Such programs are able to reach older adults who are unable
or unwilling to participate in community-based group exercise (Etkin, Prohaska,
Harris, Latham, & Jette, 2006).
Promising results have been found in some home-based programs for older
adults. For example, the strong-for-life program, a home-based resistance
exercise program, was effective in reducing physical disability among White older
adults (Jette, et al., 1999). For interventions utilizing both supervised center-and
home-based formats among high functioning older adults, greater participating
rates were found in the home-based program (Brawley, et al., 2003). Most of the
interventions, however, have not targeted or included substantial numbers of frail
and ethnically diverse older adults (King et al., 1998; Glasgow, et al., 2003;
Yancey et al., 2004; Marcus et al., 2006).
The Healthy Moves for Aging Well program (Healthy Moves), a home-based
low-intensity strength training program, was developed to address this research
gap by targeting nursing home certifiable older adults living in the community and
participating in a Medicaid waiver program. The aim of the study was to assess the
29
effectiveness of the Healthy Moves program in improving measures of health
outcomes among the participants.
B. Methods
The Healthy Moves program was designed and piloted by the Partners in
Care Foundation, a non-profit organization with an extensive history in testing,
adapting and disseminating evidence-based models. It was evaluated by an
outside evaluation team at the University of Southern California. Healthy Moves
began on July 1, 2004 and was completed on January 31, 2008.
Study Participants
The Healthy Moves program targeted low-income, nursing home certifiable
individuals dually eligible for Medicare and Medicaid from four California’s
Multipurpose Senior Services Program (MSSP) sites. MSSP is a Medi-Cal
(California’s term for Medicaid) waiver program that provides care management
and purchase of services to eligible disabled, low-income older adults aged 65 and
over. MSSP participants are community- dwelling older adults who have
demonstrated significant functional impairment to qualify as nursing home
certifiable as evidenced by 1) two or more activities of daily living impairments, or
2) at least one activity of daily living deficiency and cognitive impairment.
To be eligible for the Healthy Moves program, participants had to be able to
consent to participate, and be cognitively capable of following instructions.
Participants were excluded if they were bed-bound or severely cognitively
impaired. Caregivers in the home were not required, however, participants who
30
lived alone or had no caregiver available needed to be able to stand and to
exercise alone safely.
Study Design and procedure
The Healthy Moves evaluation included a pre-test, and a 3-month post-test.
The study was approved by the institutional review boards at Partners in Care
Foundation and at the university conducting the outside evaluation. In addition, all
study participants completed a written informed consent form.
As few of the existing physical activity programs have targeted high-risk,
nursing home certifiable population in home-based settings, no optimal types of
physical activity or exercise have been recommended for this population. For the
Healthy Moves program, two simple low-intensity exercises, arm curl and seated
step-in-place adapted from the Senior Fitness Test (SFT) (Rikli & Jones, 1999),
were used to improve participants’ upper and lower body strength. Due to the
frailty and safety concerns about falls, participants performed the arm curls using
one-pound weights and the steps-in-place exercise in the seated position.
Participants were encouraged to complete the exercises three to five times a week
on their own at home or in the company of their caregiver or family member, five to
ten minutes for each time, twice per day, in the morning and in the afternoon.
Healthy Moves used a combination of cognitive and behavior change
strategies to help participants develop behavioral skills needed to build the
low-intensity physical activity into their daily lives. A behavior change counseling
method called Brief Negotiation (Runkle, Osterholm, Hoban, McAdam, & Tull,
2000) was used to evoke and support participants’ internal motivation to change.
31
The central tenet of the brief negotiation model is that health care providers can not
change clients’ behavior until clients decided for themselves to change (Runkle et
al. 2000). The brief negotiation model offers a strategy for providers to lower
resistance by explaining and encouraging participants’ readiness to change and
providing personal supports. Readiness to change was measured using a ruler
scaled 0 to 10, where “0” is not ready and “10” is very ready. In addition, feedback,
social supports and helping participants set realistic goals, such as walking in the
home without falling, pouring a drink from a carton, and getting to the toilet, were
used to maximize participants’ adherence to the intervention.
Volunteer coaches were recruited and trained to deliver the counseling and
to motivate participants to change their behavior. Potential volunteer coaches
were selected based on their interests, ability to participate in the two-day training
session, commitment to complete the program, and perceived ability to lead and
motivate participants. Background in health or fitness was not required. Strategies
employed in recruiting coaches included word of mouth, Internet postings,
newspaper articles, agency newsletters, and through the volunteer pool at the four
participating sites. No financial incentives or complimentary rewards were given to
the volunteer coaches. A total of 97 volunteer coaches were recruited.
Prior to the implementation of the Healthy Moves program, care managers
at the four participating MSSP sites and volunteer coaches attended a mandatory
training workshop to learn fundamental issues related to the program, such as
instructions about the exercise, safety guidelines, barriers to behavior change, and
techniques for using the brief negotiation. Two types of volunteer coaching
32
strategies were used to encourage and motivate participants: 1) a combination of
face-to-face, on-site instruction and phone coaching (face-to-face) and 2)
telephone coaching only (phone). Face-to-face volunteer coaches taught the
participants the exercises in person, made home visits or phone calls on
scheduled appointments. Where phone coaching was used, participating site care
managers taught the exercises and volunteer coaches made motivating phone
calls without any face-to-face contacts with the participants. Both types of
volunteer coaches were asked to contact participants weekly for the first two
months and biweekly for the 3
rd
month. During each contact, the coach monitored
the participant’s progress with the exercises, engaged participants in goal-setting
discussions to support adherence, encouraged the participate to come up with
solutions to challenges, offered social support and recommendations when
appropriate, and built confidence in the participates’ ability to make positive
changes. Volunteer coaches and participants were matched based on their
cultural and language backgrounds. Seven different languages were used in the
intervention: English, Spanish, Russian, Korean, Armenian, Chinese, and Farsi.
Statistical Analysis
Outcome Measures
Participants completed the pretest and the 3-month posttest assessments
at their home. For participants who used face-to-face coaching, the volunteer
coaches administered their assessments. For participants who used phone
coaches only, care managers administered their assessments. The present study
included the following measures: exercise performance measured by the number
33
of arm curls in 30 seconds and number of seated steps-in-place in 2 minutes,
number of falls during the past 3 months, fear of falling, depression, and pain. The
number of falls at the pre-test and the posttest were not normally distributed. Fear
of falling and depression were measured by scores on a 3-point Likert rating with
responses ranging from 1 = none of the time to 3 = most or all of the time. Pain was
measured with a 10-point scale, with a higher number indicating a higher level of
pain.
Change analysis
To address the changes from pretest to posttest in the number of falls, fear
of falling, and depression, nonparametric Wilcoxon signed rank tests were first
employed to analyze the unadjusted changes. A paired t-test was conducted to
analyze the unadjusted mean changes of pain level from pretest to posttest.
Repeated measures ANCOVAs using SAS PROC GLIMMIX (SAS 9.2) were then
conducted to measure the adjusted changes controlling for age, gender, race, and
functional status measured by number of limitations in activities of daily living
(Katz, Ford, Moskowitz, Jackson, & Jaffe, 1963) and Instrumental Activities of
Daily Living (IADLs) (Lawton, & Brody, 1969). The ADLs included dressing, eating,
bathing, toileting, transferring from bed to chair and grooming. The IADLs included
using the telephone, laundry, transportation, shopping, preparing meals,
housekeeping, taking medications, and handling finances. Missing values for
ADLs (9.45%) and IADLs (8.85%) were imputed by matching the response
patterns of persons with complete data to persons with missing data.
34
To determine if there was any association between the two low-intensity
exercise and the changes of health outcome, the changes of the health outcomes
were further analyzed respectively among participants who had improvement, no
change, and decline in both of the exercise
performance.
C. Results
Participant Retention
As shown in Figure 3, 865 participants were recruited into the study; 157
who did not meet the inclusion criteria were excluded. Among these, 118 were
receiving occupational therapy and physical therapy; 38 were in the Integrated
Care Management program (ICMP), and 1 was bed-bound. Of the individuals who
were eligible for the study (n=708), 190 declined to participate and 518 participants
(73.2%) were included in the pre-test analysis.
Of the 518 participants who enrolled, 338 (65.3%) completed the study.
Among those who did not complete follow-up, 24.4 % (n=44) were no longer
interested; 22.2 % (n=40) could not be reached; 21.7 % (n=39) identified health
problems including pain, heart surgery and stroke; 12.2 % (n=22) left because of
staff turnover; 10.0% (n=18) were terminated from the MSSP program; 3.0 % (n=7)
died and 2.7 % (n=5) were placed in nursing facilities (See figure 3).
35
Figure 3. CONSORT Diagram of Healthy Moves

Table 4 shows selected socio-demographic characteristics of participants
at the pretest. The mean age was 80 years; 84 percent were female; more than
40% were Hispanic. Almost half of the participants were widowed. Compared to

Assessed for Eligibility (n=865)
Eligible (n=708)
 Declined to
participate
(n=190)
Included in Pre-test Analysis (n=518)
 86.68 % completed both arm curl and seated
steps-in-place (n=449)
 94.98 % completed Arm-curl (n=492)
 91.70 completed seated steps-in-place
(n=475)
Lost to Post-test (n=180)
 Not interested in the program (n=44)
 Could not be reached (n=40)
 Could not continue due to health problems
(n=39)
 Staff turnover (n=22)
 Terminated in MSSP program (n=18)
 Died (n=7)
 Entered Nursing Facilities (n=5)
 No reason given (n=5)
Included in Post-test Analysis (n=338)
Excluded (n=157)
 Not meeting
inclusion criteria
(n=157)
36
those who completed the intervention, participants who did not complete the study
were more likely to be Hispanics, and had more ADL and IADL limitations.
Table 4. Participant Characteristics at Pretest of the Healthy Moves
Intervention
Characteristics
Total
(n=518)
Completers
(n=338)
Non-Completers
(n=180)

p Value
*

Age in years, Mean
(SD) 80.1(7.25) 80.4(7.3) 79.79 (7.3)
.36
Gender, %

Men 16.23 14.5 19.4
.15
Women 83.78 85.5 80.6

Race/Ethnicity, %

White 25.48 24.9 26.7
<.001
African American 22.20 27.8 11.7

Hispanic 40.54 36.7 47.8

Other 8.11 6.8 10.6

Unknown 3.67 3.9 3.3

Marital Status, %

Married 21.24 19.5 24.4
.57
Not Married 74.13 76.1 70.6

Unknown 4.63 4.4 5.0

Limitations in ADLs, %
.03
0-3 9.65 11.5 6.1

4 14.09 16.0 10.6

5 37.84 38.8 36.1

6 28.96 25.7 35.0

Unknown 9.46 8.0 12.2

Limitations in IADLS, %

0-5 9.26 11.3 5.5***
<.001
6 11.39 14.5 5.6

7 27.99 28.7 26.7

8 41.51 37.3 49.4

Unknown 9.85 8.3 12.8

Note: *Significant difference between completers and non-completes.

Changes of the health outcomes
Table 5 shows the unadjusted mean scores of health outcomes at pretest
and posttest among participants who completed the study. The number of falls
significantly declined from pretest to 3-month posttest. About one in eight or 13%
37
of the participants fell once during the three months prior to completing the pretest
of the study. Approximately 7% had more than one fall prior to pretest. After
participating in the program, 3-month posttest results showed that the percentage
that had one fall decreased slightly to 11% and the percent who had more than one
fall decreased to 3% at posttest. A significant decline was also found in
participants’ average pain level during the 3-month intervention. Although fear of
falling and depression also declined from pretest to posttest, the changes were not
statistically significant. Similar results were found from the adjusted mean changes
from pretest to posttest, after controlling age, gender, race/ethnicity, ADLs and
IADLs (See table 6).
Table 5. Unadjusted Changes of Health Outcomes from Pretest to 3-Month
Posttest of Healthy Moves

Outcome Pretest 3-Month Posttest
Number of falls in the past three months (n=328), %
**

0 80.5 85.4
1 12.5 11.6
2+ 7.0 3.0
Fear of falling (n=332), %
None of the time 30.1 32.2
Some of the time 45.2 45.8
Most or all of the time 24.7 22.0
Depression (n=306), %
None of the time 48 53.3
Some of the time 44.5 38.2
Most or all of the time 7.5 8.5
Pain (n=325), (Mean, SD)
*
5.5(2.8) 5.1(2.9)
Note: For persons with complete data at baseline and 3-month follow-up. N’s vary because of
variation in the number of persons who answered each question completely at baseline and
3-month posttest.
* Significant change from pretest to 3-month posttest at P<0.05.
** Significant change from pretest to 3-month posttest at P<0.01.

38
Table 6. Adjusted Mean Pre-and Posttest Scores With Standard Errors for Healthy
Moves

Outcome
Pretest Posttest
P Mean SE Mean SE
Number of falls in the past three months,
(n=315) 0.28 0.15 0.17 0.15 .03
*

Fear of falling, (n=320) 1.96 0.18 1.46 0.14 .14
Depression, (n=295) 1.68 0.12 1.63 0.12 .21
Pain, (n=313) 6.06 0.56 5.71 0.56 .03
*

Note: * p is for changes from pretest to posttest. All means and standard errors for the total
sample were adjusted for age, gender, race/ethnicity, coaching, ADLs and IADLs.

The changes in health outcomes were further analyzed based on participants’
exercise performance (table not shown). Number of falls and average pain level
significantly declined among participants who improved their exercise
performance. No statistically significant changes, however, were found among
participants who had no change or decline in exercise performance. This finding
suggests that the low-intensity exercises were associated with the decline in the
number of falls and pain level among high-risk participants.
D. Discussion
The study suggests that a home-based low-intensity strength exercise
program offers a promising strategy for achieving physical-activity related health
benefits among functionally impaired nursing home certifiable older adults. Results
suggested that the Healthy Moves program benefited its participants by
significantly reducing their number of falls and pain level among participants who
improved their exercise performance.
Because the Healthy Moves intervention is extremely modest, it is
impressive that it produced such promising results. The success of the program
39
may hinge on being able to build participants’ confidence and capacity during the
three months of participation. The intervention was tailored to participants’
preference and the exercises used in the program were specially designed to be
simple and safe to engage in. Through the use of the behave change counseling
“brief negotiation” delivered by volunteer coaches, the program was able to keep
the participants engaged in doing the exercises. Furthermore, considering the
diversity of language and cultural background of the participants, all the program
handouts were translated into seven different languages including English,
Spanish, Russian, Korean, Armenian, Chinese, and Farsi. And volunteer coaches
and participants were matched based on their cultural and language backgrounds.
It is important to recognize several limitations in the study. First, Healthy
Moves is a community-developed pilot study that used a single study group.
Therefore, the intervention needs further testing using a randomly controlled trial
(RCT), to control for extraneous factors which may have influenced the change in
health status and functioning. This study was conducted among diverse frail
elders enrolled in a Medicaid waiver program in a large urban city and may not be
generalizable to other populations and settings. Although the change in pain level
was statistically significant, this change may not represent a clinically meaningful
decrease in pain, thus this findings needs to be interpreted cautiously. Another
limiting factor is in the collection of data. The outcome data were collected by those
conducting the intervention, which can potentially introduce bias. Future studies
should include independent measures of performance by an outside evaluation
team. Finally, the exercises used were adapted from the SFT (Rikli & Jones, 1999)
40
originally developed as a fitness measure and not as an exercise program. Prior to
the use of these exercises in future studies, they should be examined by
physiology experts to determine their safety and potential for use among this frail
population.
This pilot study suggests that a home-based, low-intensity strength
exercise program can benefit high-risk, ethnically diverse older adults, coupling
with behavior-change counseling services. Based on this initial success, the
program should be further developed and rigorously tested.

41
CHAPTER IV. MOTIVATING FRAIL OLDER ADULTS TO EXERCISE:
COACHING MATTERS
A. Introduction
During the past decade, a number of efforts have been made to promote
physical activity among older adults in order to improve overall health and
functional independence. The number of older adults engaging in regular physical
activity, however, remains low. About 75% of adults aged 65 and over do not meet
the recommended physical activity level (Kruger, Carlson, & Buchner, 2007).
Barriers to improving older adults’ physical activity include lack of motivation for
initiating exercise and maintaining the motivation for adherence (Brawley, et al.,
2003).
Physical activity interventions using tailored cognitive-behavioral strategies
based on social learning /social cognitive theory (Bandura, 1986) and the
transtheoratical model (Prochaska & DiClemente, 1983; Prochaska, DiClemente,
& Norcross, 1992) have been effective in increasing initial and longer-term
physical activity participation among older adults (King et al., 1998; Macus et al.,
2006). The cognitive and behavior strategies included readiness to change, goal
setting, self-monitoring, feedback, and social support. These interventions have
used a range of communication channels, including traditional face-to-face on-site
instruction (Stewart et al., 1997), mediated instruction such as the telephone (King
et al., 2000; Stewart et al., 2001) to deliver advice and support to older adults, or
the combination of both (Jette et al., 1999). Although face-to-face interventions
have the ability to provide individualized immediate feedback, personalized
42
contact, and concentrated information, barriers exist in administering face-to-face
interventions, including time limitations, cost, and limited access (Marcus, Owen,
Forsyth, Gavill, & Fridinger, 1998). Studies indicate that older adults prefer
home-based physical activity interventions with some level of instruction (Wilcox,
King, Brassington, & Ahn, 1999; King et al.; 2000). Ongoing telephone supervision
of home-based physical activity has been shown to be an effective alternative
strategy to face-to-face on-site instruction in promoting ongoing exercise
adherence (King, et al., 1998; King 2001). For example, inclusion of brief
telephone contacts along with initial face-to-face intervention enhanced adherence
rates in a home-based program of physical activity (Jette, et al., 1999).
Although mediated interventions have the potential to reach the
underserved population segments at low cost (Marcus et al., 1998), these
interventions, however, have not targeted high-risk older adults, such as frail,
homebound elders, and racial/ethnic minorities (King, 2001). The Healthy Moves
for Aging Well program (Healthy Moves) was designed to address this research
gap by targeting nursing home certifiable older adults in a Medicaid waiver
program. Two types of intervention coaching channels were delivered by volunteer
coaches: a combination of face-to-face on-site instruction with telephone coaching
(face-to-face) and telephone coaching only (phone). The aims of the study were to
determine (1) if the program could motivate frail older adults to initiate and sustain
two exercises-one targeting upper-body strength and the other one targeting
lower-body strength; and (2) to compare the differential effects of two coaching
channels on changes of the exercise performance. Previous studies suggest that
43
intervention channels with in-person social connectedness work better than those
without such contact, for example telephone versus print delivery (Marcus et al.,
2007). Building upon this, the current study examined whether a face-o-face
coaching would outperform telephone coaching alone because of the potential for
increased support and in-person connectedness between the face-to-face
coaches and participants.
B. Methods
Study design
Healthy Moves used a quasi-experimental design incorporating a pretest
and a 3-month posttest, and a 6-month follow-up from the pretest. The study was
conducted by Partners’ in Care Foundation at four sites of the Multipurpose Senior
Services Program (MSSP), a California Medicaid Waiver program. Data
management and statistical analyses were performed at the University of
Southern California (USC). The study was approved by the institutional review
boards of USC and of Partners in Care Foundation. All study participants
completed a written informed consent form.
Study Participants
Detailed information about the study participants has been described in
Chapter III. Briefly, inclusion criteria were having an age of 65 years or over;
having at least two or more activities of daily living impairments, or at least one
deficiency in activity of daily living plus cognitive impairment; willingness to
participate; and cognitively capable of following instructions. Participants were
ineligible if they were bed-bound or severely cognitively impaired. Caregivers in
44
the home were not required. However, if participants lived alone or had no
caregiver available, they needed to be able to stand unassisted in order to
exercise alone safely.
Participating site care managers were responsible for recruiting its
participants. Financial assistance was provided to the participating sites and their
care mangers. Of the 865 participants who were initially recruited into the study, a
total of 518 participants (73.2%) were included in the pre-test analysis. Three
hundred and thirty eight of them (65.3%) completed the study.
Intervention
The intervention components of the Healthy Moves project have been
discussed in detail in Chapter III. Briefly, two low-intensity exercises, arm curl
using one-pound weights and seated step-in-place, were used to improve
participants’ upper and lower body strength. A behavior change counseling
method called Brief Negotiation (Runkle, et al., 2000) was used to evoke and
support participants’ internal motivation to change. Feedback, social support, and
helping participants set realistic goals, such as walking in the home without falling,
pouring a drink from a carton, and getting to the toilet, were used to maximize
participants’ adherence to the intervention. Volunteer coaches were asked to
contact participants weekly for the first two months and biweekly for the third
month. They encouraged participants to perform the two exercises three to five
times a week. The ultimate goal was to motivate participants to be physically active
on their own without any assistance or motivation from the motivational coaches.
Statistical Analysis
45
Outcome Measures. Participants completed the pretest and the 3-month
posttest assessments in their homes. For participants motivated by the
combination of face-to-face and phone coaching, volunteer coaches administered
the assessments. For participants who used phone coaches only, care managers
administered the assessments. The performances for the two exercises, number
of arm curls in 30 seconds and number of seated steps-in-place in 2 minutes, were
measured at the pretest and the 3-month posttest. Paired t-tests were employed to
analyze changes in the exercise performance from pretest to posttest for the total
sample and by the two delivery channels. To compare the two delivery channels
associated with the changes in exercise performance, two multiple regression
models were conducted, controlling for age, gender, race, and functional status
measured by the number of limitations in activities of daily living (ADLs) (Katz, et
al.,1963) and Instrumental Activities of Daily Living (IADLs) (Lawton, & Brody,
1969). The ADLs included dressing, eating, bathing, toileting, transferring from
bed to chair and grooming. The IADLs included using the telephone, laundry,
transportation, shopping, preparing meals, housekeeping, taking medications, and
handling finances. Missing values for ADLs and IADLs (10%) were imputed by
matching the response patterns of persons with complete data to persons with
missing data.
46
C. Results
Participant Characteristics
Table 7 shows selected socio-demographic characteristics of participants
at the pretest. The mean age was 80 years (standard deviation [SD] 7.3, range
65-103 years); 84 percent were female; more than 40% were Hispanics. Almost
half of the participants were widowed. Significant variation was found across
MSSP sites using different delivery channels. Compared to participants motivated
by phone coaching only, participants who had face-to-face coaching were older; a
higher percentage were female, White, not married, and had six ADL limitations
and eight IADL limitations. Compared to those who completed the intervention,
participants who did not complete the study were more likely to be Hispanic, and
had more ADL and IADL limitations. Although a higher percentage of people who
received phone coaching dropped out of the study, compared to those who
received face-to-face coaching, the difference was not statistically significant
(p=0.19).

47
Table 7. Characteristics of the Sample for Healthy Moves at Pretest by Coaching

Characteristics
Total
(n=518)
Combination of
Face-to-Face
and Phone
Coaching
(n=118)
Phone
Coaching
(n=400)

Completers
(n=338)

Non-Completers
(n=180)
Age in years, Mean
(SD) 80.1(7.25) 82.70(7.03) 79.46(7.16)*** 80.4(7.3) 79.79 (7.3)
Gender, %
Men 16.23 10.17 18.00* 14.5 19.4
Women 83.78 89.83 82.00 85.5 80.6
Race/Ethnicity, %
White 25.48 58.47 15.75*** 24.9 26.7***
African American 22.20 13.56 24.75 27.8 11.7
Hispanic 40.54 19.49 46.75 36.7 47.8
Other 8.11 7.63 8.25 6.8 10.6
Unknown 3.67 0.85 4.50 3.9 3.3
Marital Status, %
Married 21.24 17.80 22.25** 19.5 24.4
Not Married 74.13 82.20 71.75 76.1 70.6
Unknown 4.63 0.0 6.00 4.4 5.0

48
Table 7, Continued
Limitations in ADLs, %
0-3 9.65 15.26 8.00*** 11.5 6.1*
4 14.09 3.39 17.25 16.0 10.6
5 37.84 28.81 40.50 38.8 36.1
6 28.96 49.15 23.00 25.7 35.0
Unknown 9.46 3.39 11.25 8.0 12.2
Limitations in IADLS, %
0-5 9.26 12.71 19.6*** 11.3 5.5***
6 11.39 10.17 24.4 14.5 5.6
7 27.99 27.97 33.9 28.7 26.7
8 41.51 45.76 13.4 37.3 49.4
Unknown 9.85 3.39 8.7 8.3 12.8
*p<.05; **p<.01;***p<.001.
49

Changes of Exercise Performance
Table 8 shows the changes in exercise performance among participants
who completed the study from pretest to posttest overall. Participants significantly
improved their number of arm curls in 30 seconds from pretest to posttest
(p=0.03). In contrast, their number of seated steps-in-place in 2 minutes
significantly declined from pretest to posttest (p=0.02). Significantly different
patterns were found, however, in changes of exercise performance by the two
delivery channels. Improvements in performance for upper and lower body
exercises were found among participates in face-to-face coaching (p<.01). Among
participants who used phone coaches, no significant improvement was found in
the mean number of arm curls in 30 seconds from pretest to posttest (p=0.94) and
their mean number of seated steps-in-places in 2 minutes significantly declined
(p<.0001).

50
Table 8. Changes of Functional Performance from Pretest to Posttest of Healthy Moves

Arm Curl Seated Steps-in-place
Total
Sample
Face-to-Face
and Phone
Coaching
Phone
Coaching
Total
Sample
Face-to-Face
and Phone
Coaching
Phone
Coaching
n 326 81 245 283 77 206
Pretest,
Mean(SD) 15.26(7.31) 14.44(5.98) 15.53(7.69) 44.57(31.85) 37.88(26.64) 47.07(33.30)
Posttest,
Mean(SD) 16.06(7.47) 17.54(6.34) 15.57(7.75) 40.17(31.40) 47.86(32.07) 37.29 (30.74)
t(p value) 2.14(0.03)
*
5.57(<.0001)
***
0.07(0.94) -2.39(0.02)
*
3.33(0.001)
**
-4.52(<.0001)
***

Note: * Significant change from pretest to 3-month posttest at P<0.05.
** Significant change from pretest to 3-month posttest at P<0.01.
*** Significant change from pretest to 3-month posttest at P<0.001.
51
Two multiple regression models were conducted to determine if the two
different coaching channels associated with changes in the exercise performance
remained, after controlling age, gender, race/ethnicity, ADLs, and IADLs (see table
9). Significant coaching differences were found in predicting the changes of the
exercise performance. Compared to phone coaching, face-to-face coaching was
associated with a higher number of both arm curls and seated steps-in-place at the
post-test intervention.
Table 9. Multiple Regression Models Predicting Changes of Arm Curl and Seated
Steps-in-Place of Healthy Moves

Independent Variable
Model1: Changes of arm curl
(n=313)
Model2: Changes of Seated
Steps-in-place
(n=273)
b SE b SE
Combination of
Face-to-face and Phone
coaching 2.90 1.01** 17.71 4.79***
Age in Years -0.07 0.05 0.17 0.26
Female 2.84 1.11* 4.95 5.37
Race: (vs. White)
African American 0.29 1.14 6.69 5.48
Hispanic -1.00 1.07 -9.00 5.13
Other -1.09 1.61 -5.12 7.84
ADL Limitations 0.18 0.37 1.44 1.78
IADL Limitations -0.63 0.40 2.02 1.89
Missing ADL Limitations -0.41 1.43 -0.09 7.27
Intercept 6.96 4.94 -45.68 24.21
*p<.05; **p<.01; ***p<.001.

52
D. Discussion
There is a great need to create and develop intervention methods and
strategies to motivate underserved populations to be physically active (Prohaska
et al., 2006). The current study was undertaken to determine if a home-based
low-intensity strength training program could motivate high-risk older adults to
improve performance in upper and lower body strength. Through the use of
cognitive and behavior strategies delivered by volunteer coaches, a high
completion rate was achieved among these high-risk older adults, with more than
65% of the participants completing the study.
Previous studies suggest that phone coaching is an effective method of
motivating participants to be physically activity in home-based exercise programs
(King, Haskell, Young, Oka, & Stefanick, 1995). Results from the present study,
however, showed that participants who were motivated by face-to-face coaching
did better in their exercise performance, compared to those coached via phone.
One potential explanation for the difference was that participants who were
motivated by face-to-face coaching may be more willing to adhere to the exercise
program due to in-person contacts with their coaches, compared to those who
never had any face-to-face contact with their coaches.
It is important to recognize several limitations in the study. First, Healthy
Moves is a community-developed pilot study that used a single study group.
Therefore, the intervention needs further testing using a randomly controlled trial
(RCT), to control for extraneous factors which may have influenced the change in
exercise performance. This study was conducted among diverse frail elders
53
enrolled in a Medicaid waiver program in a large urban city and may not be
generalizable to other populations and settings. In addition, the exercises used
were adapted from the SFT
16
originally developed as a fitness measure and not as
an exercise program. Prior to the use of these exercises in future studies, they
should be examined by physiology experts to determine if they are the most
appropriate exercise for use among this frail population.
As one of the first evaluation of a home-based exercise intervention with a
nursing home certifiable sample, the results show that a low-intensity strength
training program could motivate high-risk older adults to improve performance in
upper and lower body strength. Face-to-face coaching appears to be a more
powerful motivator than a telephone-based approach only. The evaluation
suggests that, for this population, face-to-face contacts may be worth additional
costs to ensure a positive outcome. Based on the initial finding of the pilot study, a
more rigorous design should be further developed in the future.

54
CHAPTER V. DISCUSSION
This dissertation examined the translation of research into practice by
evaluating two physical activity programs for older adults that were implemented in
in-home and community-based settings. Chapter I described the research
background and the REAIM conceptual framework guiding the translational
research. Chapter II reported the results of the outcome evaluation from the Active
Start program. Active Start targeted sedentary or under-active community-dwelling
older adults aged 50 years and over. It used a multifaceted approach to recruit
participants, including project presentations, flyers, brochures/catalogs, and word
of mouth. The intervention incorporated a behavior change class (ALED) and a
fitness class (ExerStart) specially designed for sedentary older adults. Ninety-six
percent (n=208) of the participants participated in the study. Results show that
participation in Active Start produced significant improvement in physical
performance measuring strength, flexibility and balance among overall
participants and by race/ethnicity. It suggests that a community-based physical
activity program benefits sedentary, ethnically diverse older adults by coupling
fitness classes and a behavioral change support group.
Chapter III reported the outcome evaluation from the Healthy Moves
program. Healthy Moves targeted low-income high-risk home-dwelling older adults
enrolled in four of California’s MSSP sites. Two low-intensity exercises, arm curls
using one-pound weights and seated steps-in-place, were used to improve
participants’ upper and lower body strength. A behavior change counseling
method called Brief Negotiation (Runkle, et al., 2000) was used to evoke and
55
support participants’ internal motivation to change. Two types of volunteer
coaches were used to deliver these counseling strategies: 1) the combination of
face-to-face, on-site instruction with phone coaching and 2) ongoing telephone
coaching without any in-person contacts. Strategies employed in recruiting
coaches included word of mouth, Internet postings, newspaper articles, and
agency newsletters. There were also volunteer pools at the four participating sites.
The evaluation shows that participants had significant decline in the number of
falls and pain level. The significant declines were found among participants who
improved their exercise performance. More than 73% of the participants (n=518)
participated the study. Exercise performance varied by the two coaching channels.
Therefore, chapter IV was conducted to determine the different effects of the two
coaching channels on exercise performance. Results show that individuals with
the combination of face-to-face with phone coaches had a better exercise
performance, compared to those motivated by phone coaching alone.
Strengths and Limitations of the Dissertation
This study has several strengths that contribute to a broader
knowledge base in translating evidence-based health programs into practice. First,
there is a great need in translational research providing greater representation of
minority and disadvantaged older populations (Prohaska, et al., 2006). This
dissertation study provides important new evidence that culturally appropriate
physical activity programs are promising and effective strategies for promoting
physical activity and achieving physical-activity related health benefits among
ethnically diverse and high-risk older adults in the community. Second, both of the
56
physical activity programs were conducted by community agencies. The
effectiveness of the two physical activity programs further provides evidence that
can be replicated using aging network community agencies. Third, another
strength of the dissertation study is the use of rigorous quantitative methods to
measure change in pretest-posttest designs. These methods included paired
t-tests, non-parametric statistical analyses and repeated measures ANCOVAs
using SAS Proc Mixed for normally-distributed interval data and proc GLIMMIX for
not normally distributed categorical data. The use of repeated measures
ANCOVAs reported the adjusted changes of measurement, controlling for other
factors. Compared to SAS proc GLM, proc Mixed reports least square means and
estimates of linear combinations with correct standard errors (UCLA: Academic
Technology Services, Statistical Consulting Group, 2008).
There were also a few limitations to note in this dissertation. First, both of the
interventions were not randomly controlled. Therefore, the interventions need to
be further tested in a randomly controlled trial (RCT) before generalizing the
findings of the study. Second, for the Healthy Moves study, the participants’
sociodemographic information came from the care management database of the
four MSSP sites. However, all sites were required by the state to use the database
for billing purposes. Therefore, additional variables on health status of the
participants were not available. Third, guided by the REAIM framework, this
dissertation research reported the target population and the recruitment strategies
(Reach), examined the effectiveness of the two interventions, described the
participation rate and characteristics of intervention agents (Adopt), and identified
57
essential intervention elements (Implementation). However, as both of the two
physical activity interventions were short term (less than 6 month), the long-term
effects of the interventions (Maintenance) are unknown.
Future Research: Sustainability
Sustainability of effective physical activity programs plays a critical role in
maintaining the long-term effects of the interventions for older adults. However,
difficulties were encountered in sustaining the two physical activity programs. Both
the Healthy Moves and Active Start programs were discontinued at the end of their
research funding. In addition, with the termination of the two programs, both of
their program coordinators/mangers have left their agencies, which conducted the
interventions. The turnover of the key personnel further challenges the
sustainability of the programs.
Having an innovative community-based program with demonstrated
success is not sufficient to assure its’ long-term existence (Prohaska & Etkin,
2004). Financial self-sufficiency and low turn over of key personnel are essential to
maintaining programs over time. In addition, program sustainability is more likely
when there is a collaboration among researchers, local funding agencies,
community organizations and practitioners (Evashwick & Ory, 2003; Prohaska &
Etkin, 2004). Strategies in building sustainable evidence-based health programs
should be addressed in future studies.
58
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Asset Metadata

Creator Yan, Tingjian (author)

Core Title Translating two physical activity programs for older adults into home- and community-based settings: "Active Start" and "Healthy Moves for Aging Well"

School Leonard Davis School of Gerontology

Degree Doctor of Philosophy

Degree Program Gerontology

Publication Date 05/12/2009

Defense Date 01/16/2009

Publisher University of Southern California (original), University of Southern California. Libraries (digital)

Tag Active Start,Healthy Moves for Aging Well,intervention,OAI-PMH Harvest,physical activity

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Wilber, Kathleen H. (committee chair), Nichol, Michael B. (committee member), Pynoos, Jon (committee member)

Creator Email jessieyan1002@gmail.com,tingjiay@usc.edu

Permanent Link (DOI) https://doi.org/10.25549/usctheses-m2242

Unique identifier UC1279514

Identifier etd-Yan-2803 (filename),usctheses-m40 (legacy collection record id),usctheses-c127-237196 (legacy record id),usctheses-m2242 (legacy record id)

Legacy Identifier etd-Yan-2803.pdf

Dmrecord 237196

Document Type Dissertation

Rights Yan, Tingjian

Type texts

Source University of Southern California (contributing entity), University of Southern California Dissertations and Theses (collection)

Repository Name Libraries, University of Southern California

Repository Location Los Angeles, California

Repository Email cisadmin@lib.usc.edu